activity
20022024
most citedPlanck 2015 results. XIII. Cosmological parameters

10.6k citations · 20.6k across the 42 of their papers we have counts for

collaborators

42 papers

astro-ph.CO2024★ 550 cited

Euclid. I. Overview of the Euclid mission

Euclid Collaboration, Y. Mellier, Abdurro'uf +1134

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Eucl…

astro-ph.CO2022★ 7 cited

BeyondPlanck IV. On end-to-end simulations in CMB analysis -- Bayesian versus frequentist statistics

M. Brilenkov, K. S. F. Fornazier, L. T. Hergt +48

End-to-end simulations play a key role in the analysis of any high-sensitivity CMB experiment, providing high-fidelity systematic error propagation capabilities unmatched by any ot…

astro-ph.IM2022★ 22 cited

Euclid preparation: XXII. Selection of Quiescent Galaxies from Mock Photometry using Machine Learning

Euclid Collaboration, A. Humphrey, L. Bisigello +206

The Euclid Space Telescope will provide deep imaging at optical and near-infrared wavelengths, along with slitless near-infrared spectroscopy, across ~15,000 sq deg of the sky. Euc…

astro-ph.CO2022★ 17 cited

BeyondPlanck XI. Bayesian CMB analysis with sample-based end-to-end error propagation

L. P. L. Colombo, J. R. Eskilt, S. Paradiso +36

We present posterior sample-based cosmic microwave background (CMB) constraints from Planck LFI and WMAP observations derived through global end-to-end Bayesian processing. We use…

astro-ph.GA2022★ 18 cited

Euclid preparation. XXI. Intermediate-redshift contaminants in the search for galaxies within the Euclid Deep Survey

Euclid Collaboration, S. E. van Mierlo, K. I. Caputi +203

(Abridged) The Euclid mission is expected to discover thousands of z>6 galaxies in three Deep Fields, which together will cover a ~40 deg2 area. However, the limited number of Eucl…

astro-ph.IM2022★ 2 cited

BeyondPlanck V. Minimal ADC Corrections for Planck LFI

D. Herman, R. A. Watson, K. J. Andersen +36

We describe the correction procedure for Analog-to-Digital Converter (ADC) differential non-linearities (DNL) adopted in the Bayesian end-to-end BeyondPlanck analysis framework. Th…